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Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 94 - 104 Titre : Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Jean-Claude Thill, Auteur ; Sutee Anantsuksomsri, Auteur ; Nij Tontisirin, Auteur ; Ran Tao, Auteur Année de publication : 2018 Article en page(s) : pp 94 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] Birmanie [Termes IGN] Chine [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] Hevea brasiliensis [Termes IGN] image Landsat [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Laos [Termes IGN] modèle de croissance végétale [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] plantation forestière [Termes IGN] série temporelle Résumé : (Auteur) Rubber (Hevea brasiliensis) plantations are a rapidly increasing source of land cover change in mainland Southeast Asia. Stand age of rubber plantations obtained at fine scales provides essential baseline data, informing the pace of industrial and smallholder agricultural activities in response to the changing global rubber markets, and local political and socioeconomic dynamics. In this study, we developed an integrated pixel- and object-based tree growth model using Landsat annual time series to estimate the age of rubber plantations in a 21,115 km2 tri-border region along the junction of China, Myanmar and Laos. We produced a rubber stand age map at 30 m resolution, with an accuracy of 87.00% for identifying rubber plantations and an average error of 1.53 years in age estimation. The integration of pixel- and object-based image analysis showed superior performance in building NDVI yearly time series that reduced spectral noises from background soil and vegetation in open-canopy, young rubber stands. The model parameters remained relatively stable during model sensitivity analysis, resulting in accurate age estimation robust to outliers. Compared to the typically weak statistical relationship between single-date spectral signatures and rubber tree age, Landsat image time series analysis coupled with tree growth modeling presents a viable alternative for fine-scale age estimation of rubber plantations. Numéro de notice : A2018-399 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.003 Date de publication en ligne : 13/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90828 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018101	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018103	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018102	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt